Search Results for author: Franz Quint

Found 5 papers, 0 papers with code

Artificial Intellgence -- Application in Life Sciences and Beyond. The Upper Rhine Artificial Intelligence Symposium UR-AI 2021

no code implementations10 Dec 2021 Karl-Herbert Schäfer, Franz Quint

The TriRhenaTech alliance is a network of universities in the Upper-Rhine Trinational Metropolitan Region comprising of the German universities of applied sciences in Furtwangen, Kaiserslautern, Karlsruhe, Offenburg and Trier, the Baden-Wuerttemberg Cooperative State University Loerrach, the French university network Alsace Tech (comprised of 14 'grandes \'ecoles' in the fields of engineering, architecture and management) and the University of Applied Sciences and Arts Northwestern Switzerland.

Management

Artificial Intelligence: Research Impact on Key Industries; the Upper-Rhine Artificial Intelligence Symposium (UR-AI 2020)

no code implementations5 Oct 2020 Andreas Christ, Franz Quint

The TriRhenaTech alliance presents a collection of accepted papers of the cancelled tri-national 'Upper-Rhine Artificial Inteeligence Symposium' planned for 13th May 2020 in Karlsruhe.

Management

Artificial Intelligence : from Research to Application ; the Upper-Rhine Artificial Intelligence Symposium (UR-AI 2019)

no code implementations20 Mar 2019 Andreas Christ, Franz Quint

The TriRhenaTech alliance universities and their partners presented their competences in the field of artificial intelligence and their cross-border cooperations with the industry at the tri-national conference 'Artificial Intelligence : from Research to Application' on March 13th, 2019 in Offenburg.

Management

Scale-Awareness of Light Field Camera based Visual Odometry

no code implementations ECCV 2018 Niclas Zeller, Franz Quint, Uwe Stilla

The method is tested based on a versatile dataset consisting of challenging indoor and outdoor sequences and is compared to state-of-the-art monocular and stereo approaches.

Visual Odometry

A Synchronized Stereo and Plenoptic Visual Odometry Dataset

no code implementations24 Jul 2018 Niclas Zeller, Franz Quint, Uwe Stilla

We present a new dataset to evaluate monocular, stereo, and plenoptic camera based visual odometry algorithms.

Visual Odometry

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